Neuropsychiatric disorders are associated with significantly increased morbidity and mortality. Chronic complex diseases including cardiovascular disease (CVD) are the primary drivers of premature death among individuals with psychiatric disorders. While there is evidence that modifiable risk factors (i.e., smoking, weight, medication use, etc.) increase risk, they do not fully account for the excess morbidity and mortality in this population. The growing availability of large-scale biobanks linking electronic health records (EHRs) to biospecimens has created a powerful, but still relatively untapped, opportunity for psychiatric research aimed at addressing this excess morbidity and mortality. In 2007, the National Human Genome Research Institute (NHGRI) organized the Electronic Medical Records and Genomics (eMERGE) network which brought together investigators around the U.S. to facilitate EHR-based genomic research and the implementation of genomic medicine. We have created a new, large-scale collaborative consortium?PsycheMERGE?that leverages the resources and existing infrastructure of the eMERGE network, the Psychiatric Genomics Consortium (PGC), and local EHR and biobank resources. This application uses EHR and genomic data across multiple health care systems (Partners Health Care, Vanderbilt University Medical Center, and Geisinger Health Systems) that are collaborative partners in the PsycheMERGE network. Our preliminary data also demonstrates that polygenic risk for Major Depressive Disorder (MDD) is associated with important prognostic biomarkers of CVD widely available within the EHR. Building on this preliminary data, our first aim is to discover pleiotropic genes contributing to MDD risk, CVD risk, and known CVD biomarkers which we hypothesize will also point to important pathways involved in the biology of MDD. In aim 2 we employ a population epidemiological approach to investigate the moderating effects of biopsychosocial variables on the genetic and phenotypic risk factors linking MDD and CVD. Finally, in aim 3 we characterize the phenotypic and genomic relationships between each of three common severe mental illnesses, and the rest of the medical phenome including >500 clinical lab tests in over 300,000 individuals with data present in the EHR. There is an urgent public health need to improve care and treatment of psychiatric disorders and their comorbidities. The proposed research includes a comprehensive set of integrative analyses aimed at investigating the genetic, clinical, and psychosocial risk factors that contribute to the development of psychiatric disorders and their life-threatening comorbidities in the context of a national network of EHRs and associated biobanks. !